Personalized Prediction of Change in Fasting Blood Glucose Following Basal Insulin Adjustment in People With Type 2 Diabetes: A Proof-of-Concept Study
Authors' conclusion
A model using FBG, insulin doses, and blood samples can predict a five-week change in FBG after adjusting the basal insulin dose in people with type 2 diabetes. Implementation of such a model can potentially help optimize titration and improve glycemic control.
Study context
- Population
- Adults with T2D treated with basal insulin; mean age ≈59 years, mean diabetes duration 12 years, mean HbA1c at screening 65 mmol/mol (8.1%)
- Participants
- 786 adults
- Outcome
- Prediction of change in FBG following basal insulin adjustment
Methodological detailsproof-of-concept, multiple linear regression, training (80%) and testing (20%) sets, forward feature selection, fivefold cross-validation
- Proof-of-concept
- Multiple linear regression
- Training (80%) and testing (20%) sets
- Forward feature selection
- Fivefold cross-validation
Performance
As reported in the abstract
Model performance for predicting change in FBG
Relative absolute error
0.67
Pearson correlation coefficient
0.74
Coefficient of determination
0.55
Original publication
Personalized Prediction of Change in Fasting Blood Glucose Following Basal Insulin Adjustment in People With Type 2 Diabetes: A Proof-of-Concept Study. J Diabetes Sci Technol. Published 2 October 2023. doi:10.
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